Cough activity detection for automatic tuberculosis screening
The automatic identification of cough segments in audio through the determination of start and end points is pivotal to building scalable screening tools in health technologies for pulmonary related diseases. We propose the application of two current pre-trained architectures to the task of cough activity detection. A dataset of recordings containing cough from patients symptomatic for tuberculosis (TB) who self-present at community-level care centres in South Africa and Uganda is employed. When automatic start and end points are determined using XLS-R, an average precision of 0.96 and an area under the receiver-operating characteristic of 0.99 are achieved for the test set. We show that ...
| Authors | Joshua Jansen van Vüren, Devendra Singh Parihar, Daphne Naidoo et al. |
|---|---|
| Primary category | eess.AS |
| Published | 11 March 2026 |
| Last updated at source | 11 March 2026 |
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